Evaluation of the treatment time-lag effect for survival data

Kayoung Park () and Peihua Qiu ()
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Kayoung Park: Old Dominion University
Peihua Qiu: University of Florida

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2018, vol. 24, issue 2, No 6, 310-327

Abstract: Abstract Medical treatments often take a period of time to reveal their impact on subjects, which is the so-called time-lag effect in the literature. In the survival data analysis literature, most existing methods compare two treatments in the entire study period. In cases when there is a substantial time-lag effect, these methods would not be effective in detecting the difference between the two treatments, because the similarity between the treatments during the time-lag period would diminish their effectiveness. In this paper, we develop a novel modeling approach for estimating the time-lag period and for comparing the two treatments properly after the time-lag effect is accommodated. Theoretical arguments and numerical examples show that it is effective in practice.

Keywords: Cox proportional hazards model; Crossing hazard rates; Lag effect; Survival analysis; Treatment comparison (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10985-017-9390-7

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